Java 8 Stream: groupingBy with multiple Collectors

Question

I want to use a Java 8 Stream and Group by one classifier but have multiple Collector functions. So when grouping, for example the average and the sum of one field (or maybe another field) is calculated.

I try to simplify this a bit with an example:

public void test() {
    List<Person> persons = new ArrayList<>();
    persons.add(new Person("Person One", 1, 18));
    persons.add(new Person("Person Two", 1, 20));
    persons.add(new Person("Person Three", 1, 30));
    persons.add(new Person("Person Four", 2, 30));
    persons.add(new Person("Person Five", 2, 29));
    persons.add(new Person("Person Six", 3, 18));

    Map<Integer, Data> result = persons.stream().collect(
            groupingBy(person -> person.group, multiCollector)
    );
}

class Person {
    String name;
    int group;
    int age;

    // Contructor, getter and setter
}

class Data {
    long average;
    long sum;

    public Data(long average, long sum) {
        this.average = average;
        this.sum = sum;
    }

    // Getter and setter
}

The result should be a Map that associates the result of grouping like

1 => Data(average(18, 20, 30), sum(18, 20, 30))
2 => Data(average(30, 29), sum(30, 29))
3 => ....

This works perfectly fine with one function like "Collectors.counting()" but I like to chain more than one (ideally infinite from a List).

List<Collector<Person, ?, ?>>

Is it possible to do something like this?

Answer 1

For the concrete problem of summing and averaging, use collectingAndThen along with summarizingDouble:

Map<Integer, Data> result = persons.stream().collect(
        groupingBy(Person::getGroup, 
                collectingAndThen(summarizingDouble(Person::getAge), 
                        dss -> new Data((long)dss.getAverage(), (long)dss.getSum()))));

For the more generic problem (collect various things about your Persons), you can create a complex collector like this:

// Individual collectors are defined here
List<Collector<Person, ?, ?>> collectors = Arrays.asList(
        Collectors.averagingInt(Person::getAge),
        Collectors.summingInt(Person::getAge));

@SuppressWarnings("unchecked")
Collector<Person, List<Object>, List<Object>> complexCollector = Collector.of(
    () -> collectors.stream().map(Collector::supplier)
        .map(Supplier::get).collect(toList()),
    (list, e) -> IntStream.range(0, collectors.size()).forEach(
        i -> ((BiConsumer<Object, Person>) collectors.get(i).accumulator()).accept(list.get(i), e)),
    (l1, l2) -> {
        IntStream.range(0, collectors.size()).forEach(
            i -> l1.set(i, ((BinaryOperator<Object>) collectors.get(i).combiner()).apply(l1.get(i), l2.get(i))));
        return l1;
    },
    list -> {
        IntStream.range(0, collectors.size()).forEach(
            i -> list.set(i, ((Function<Object, Object>)collectors.get(i).finisher()).apply(list.get(i))));
        return list;
    });

Map<Integer, List<Object>> result = persons.stream().collect(
        groupingBy(Person::getGroup, complexCollector)); 

Map values are lists where first element is the result of applying the first collector and so on. You can add a custom finisher step using Collectors.collectingAndThen(complexCollector, list -> ...) to convert this list to something more appropriate.

Answer 2

By using a map as an output type one could have a potentially infinite list of reducers each producing its own statistic and adding it to the map.

public static <K, V> Map<K, V> addMap(Map<K, V> map, K k, V v) {
    Map<K, V> mapout = new HashMap<K, V>();
    mapout.putAll(map);
    mapout.put(k, v);
    return mapout;
}

...

    List<Person> persons = new ArrayList<>();
    persons.add(new Person("Person One", 1, 18));
    persons.add(new Person("Person Two", 1, 20));
    persons.add(new Person("Person Three", 1, 30));
    persons.add(new Person("Person Four", 2, 30));
    persons.add(new Person("Person Five", 2, 29));
    persons.add(new Person("Person Six", 3, 18));

    List<BiFunction<Map<String, Integer>, Person, Map<String, Integer>>> listOfReducers = new ArrayList<>();

    listOfReducers.add((m, p) -> addMap(m, "Count", Optional.ofNullable(m.get("Count")).orElse(0) + 1));
    listOfReducers.add((m, p) -> addMap(m, "Sum", Optional.ofNullable(m.get("Sum")).orElse(0) + p.i1));

    BiFunction<Map<String, Integer>, Person, Map<String, Integer>> applyList
            = (mapin, p) -> {
                Map<String, Integer> mapout = mapin;
                for (BiFunction<Map<String, Integer>, Person, Map<String, Integer>> f : listOfReducers) {
                    mapout = f.apply(mapout, p);
                }
                return mapout;
            };
    BinaryOperator<Map<String, Integer>> combineMaps
            = (map1, map2) -> {
                Map<String, Integer> mapout = new HashMap<>();
                mapout.putAll(map1);
                mapout.putAll(map2);
                return mapout;
            };
    Map<String, Integer> map
            = persons
            .stream()
            .reduce(new HashMap<String, Integer>(),
                    applyList, combineMaps);
    System.out.println("map = " + map);

Produces :

map = {Sum=10, Count=6}